Detection and ranging systems using radio frequency energy, normally referred to as Radar systems, typically emit a modulated burst of radio frequency energy that is reflected off a target back towards an associated radio receiver. The receiver system, through a variety of demodulation and detection techniques, detects the time-of-arrival of the return signal. The difference between the time of emission and reception, often referred to as the time-of-flight or propagation delay, is used to calculate distance. At emission, these systems typically modulate a high frequency RF carrier. At reception, the carrier is mixed with a lower frequency to down-convert or frequency shift the signal to a lower, more convenient intermediate frequency. Once at the lower frequency many techniques are used to demodulate and detect the signal including direct analog-to-digital conversion and digital signal processing.
A key attribute separating RADAR systems from most optical counterparts, often referred to LIDAR systems, is ability of RF systems to coherently demodulate the RF carrier. Coherent detection allows RADAR systems the flexibility to trade the requirement for high peak power, short duration RF pulses most desirable for time-of-flight measurement for low average power, long duration signals amenable for practical implementation. The possibility of using RF transmitters that spread out RF energy bursts in time has led to a wide variety of pulse compression techniques using frequency modulation to first temporally spread the signal at transmission and at reception, time-frequency compresses the returned pulse. One popular method of signal pulse compression modulates the RF carrier with a series of frequencies or phase shifts based on a binary coding sequence. The binary encoding of the RF carrier allows the detection of a bipolar binary sequence at reception which can then be mathematically matched or correlated with a stored reference to estimate delay. The correlation process involves sweeping a signal reference pattern progressively through a signal return to generate an autocorrelation function verses time. The autocorrelation function response forms a spiked central peak with a periodic pattern of slide lobes on either side. Specific binary sequences with desirable autocorrelation properties are well known to obtain the best performance for a specific requirement. A key requirement for the implementation of these correlation sequences is the need to detect the orthogonal states of the transmitted signal in order to allow mathematical cancelation of sidelobes outside the central waveform peak. Without sidelobe cancelation, the resulting correlation forms a comb pattern with stronger correlation function peaks as the central peak is approached.
The relative lack of use of correlation techniques for time-of-flight LIDAR systems results from complexities and limitations from incoherent detection and the prohibitive cost and complexity of receivers incorporating analog-to-digital conversion. In coherent signal detection, information contained in the electromagnetic carrier can be preserved in the detection process. Preserving this carrier information allows both the efficient averaging of the received signal, the proportional increase in signal-to-noise with integration time, along with the ability to preserve the transmitted phase state. The coherent detection of the RF carrier allows the effective transmission of orthogonal carrier states, essentially allowing the transmission of the +1 or −1 states necessary for the effective use in demodulating correlation coded waveforms. Incoherent signal detection associated with typical optical receivers, such as those using a photo conductive diode results in the loss of carrier information due to the square law characteristic of the detector. With only the ability to detect the presence or lack of presence of the return signal based on a detection threshold, measurement of correlation coded waveforms is ineffective. Analog-to-digital conversion of the detector output with supporting digital post processing can be used to remove the unwanted DC component present in the optical detector signal output to allow correlation processing. Unfortunately, analog-to-digital convertors at hundreds of megahertz sample rates are still too expensive and power hungry for use in low cost optical distance systems.
A variety of approaches have been applied to adapt Radar correlation processing to direct detection optical rangefinders. U.S. Pat. No. 6,307,622 to Lewis describes the transmission of a preamble, prior to the transmission of the binary encoding correlation sequence, to allow the establishment of a detection reference level. For a period before pattern transmission, the transmitter emits a half-power output pedestal level to allow the band-pass response low-frequency cut-off of the optical receiver to return to its baseline detection level. The transmitted binary sequence has a 50% average duty cycle to prevent the baseline detection level from drifting during the burst. U.S. Pat. No. 6,411,644 to Takashi et al. describes the use of the scaled output of a signal amplitude detector to establish a detection threshold level for the received correlation sequence.
Analog-to-digital conversion of the received signal with digital post processing can be used to remove the DC offset introduced by the square-law detection of the received signal by envelope detection of the received binary correlation sequence. Once the signal envelope is known, the DC offset can be subtracted from the waveform allowing either zero crossing detection or analog correlation using a stored zero delay reference.
Excessive cost, power consumption, and complex interface requirements are often issues prohibiting the use of monolithic analog-to-digital converters in high-frequency sensor applications. At digitization rates in excess of 100 mega-samples per second, A-D converters typically cost several tens of dollars and as digitization rates approach a GHz, costs increase sufficiently to be unsuitable for many applications. Power consumption, often in excess of one watt, can be a significant limitation for battery-powered devices. Finally the interfacing of digital processing circuitry to a high-speed A-D converter dictates the use of large numbers of parallel I/O channels creating the potential for system noise issues and increased hardware complexity.
For high-speed repetitive sampling, various analog sample-and-hold methods have been used. At signal bandwidths of a GHz or more, diode samplers are often used to synchronously sample the analog signal voltage. Effective signal capture times as low as 10's of picoseconds make this method practical for direct signal digitization into the gigahertz. Historically this approach has been used in high-speed sampling oscilloscopes to digitize a waveform by scanning a narrow signal acquisition window over a larger time period. At each time point one or more analog samples are taken and subsequently the analog value is digitized using a lower-speed analog-to-digital converter. A class of low cost samplers exemplified by U.S. Pat. No. 5,757,320 to McEwen has been applied to impulse radar based distance measurement along with a variety of specialized applications.
U.S. Pat. No. 6,950,177 to Lewis et al. teaches a method to achieve high measurement accuracy using a low-cost signal digitization approach using on a single-bit comparator with an adjustable threshold reference. The sampling and processing is suitable for implementation in high performance FPGA's (field-programmable-gate-arrays) allowing a high level of hardware integration at low system cost. The method is based on the storage of a succession of histograms representing the cumulative statistics of the one/zero logical state of the comparator output. After the accumulation of data at a threshold level, the histogram data is combined with previous data. Following each series of acquisitions, the threshold level is increased and the histogram acquisition and accumulation process repeats until the threshold is swept through the entire waveform in a stepwise fashion. The method weights the most accurate data at each comparison level allowing the generation of a composite waveform with good signal fidelity. Since the incoming bit rate is significantly faster than the base clock rate of the system, a period after each signal acquisition window is required to perform a bit summation and signal reconstruction process. The use of a transmit reference waveform is disclosed to maintain measurement accuracy. The receive signal strength is measured and a transmit reference signal is matched using an adjustable optical attenuator so that the reference is roughly equal to the received signal so that both the reference and return signal experience equal propagation delays in the receiver electronics.
U.S. Pat. No. 8,125,620 to Lewis, which is incorporated herein by reference, discloses a signal reconstruction method based on signal detection using single-bit quantization processed to accumulate edge crossing states. The accumulated signal crossing statistics are processed to obtain signal shape by using the difference between rising and falling edges to estimate signal slope. Under strong signal conditions, this approach adds the feature of sweeping of the threshold detection level through the extent of the signal to prevent large signal distortion and clipping. As the slicing threshold level moves close to signal at a given sampling point, random noise produces a difference of rising and falling edge transitions proportional to the slope of the signal in that region. As the threshold matches the signal level at the sampling point, the rate of crossings disproportionately increases, effective weighting of edge data provides optimal signal to noise ratio. The estimated slope can be integrated to recover the signal waveform.